Evoked potentials (EP) are electrophysiological signals generated by the central nervous system in response to stimulation. Subspace methods in EP analysis commonly relate to the application of the singular value decomposition (SVD) to reveal the principal features of the signals. In single-channel EP analysis, the measurement matrix is constructed based on an ensemble of singletrial EPs, obtai...

This paper presents some recent filtering methods based on the lower-rank tensor approximation approach for denoising tensor signals. In this approach, multicomponent data are represented by tensors, that is, multiway arrays, and the presented tensor filtering methods rely on multilinear algebra. First, the classical channel-by-channel SVD-based filtering method is overviewed. Then, an extensio...

In this paper we employ adaptive LMS ltering for the e cient decorrelation of still images. The decorrelation algorithm is coupled with a novel entropy coder and applied to lossless image coding. The proposed scheme is shown to have comparable performance with other known algorithms for context-based image coding.

We propose a decision-feedback decoder for coded signals transmitted over finite-state Markov channels. The decoder achieves maximum-likelihood sequence detection (in the absence of feedback errors) with very low complexity by exploiting previous bit decisions and the Markov structure of the channel. We also propose a similar decoder, the output-feedback decoder, that does not use previous bit ...

To reduce interference in MIMO channels effectively and to increase the capacity of a wireless communication network using Interference alignment process. This paper refers to an enhanced Interference Alignment Scheme for a Network of MIMO Users under AWGN Interference Broadcasting Channel So Called IFBC. The Proposed Scheme Is Nuclear Norm Heuristic (NNH) process for IA K user. The process of ...

Social Tagging has become a method of choice for enriching data (like pictures) with meta-data which in turn can be used for searching (like retrieving art pictures) or tag recommendations relying on Singular Value Decompositions (SVD) to reduce dimensionality. We observed that social tagging-based search or tag-recommendation is more successful, if several dimensions describing the tagging com...

Amplitude decorrelation measurement is sensitive to transverse flow and immune to phase noise in comparison to Doppler and other phase-based approaches. However, the high axial resolution of OCT makes it very sensitive to the pulsatile bulk motion noise in the axial direction. To overcome this limitation, we developed split-spectrum amplitude-decorrelation angiography (SSADA) to improve the sig...

In this paper we present the usage of singular value decomposition (SVD) in text summarization. Firstly, we mention the taxonomy of generic text summarization methods. Then we describe principles of the SVD and its possibilities to identify semantically important parts of a text. We propose a modification of the SVD-based summarization, which improves the quality of generated extracts. In the s...

Blind source separation and blind output decorrelation are two well-known problems in signal processing. For instantaneous mixtures, blind source separation is equivalent to a generalized eigen-decomposition, while blind output decorrelation can be considered as an iterative method of output orthogonalization. We propose a steepest descent procedure on a new cost function based on the Frobenius...